将载体图像分存为多个子图像,组建多载体集,结合图像变换算法,构建基于图像分存的零隐写模型.首先选取初始载体图像,再根据需要分存为一定数量的载体子图像,任意选取一幅或多幅作为实际载体进行特定的图像变换,将隐秘图像分割后寻找图像块与图像变换后载体子图像像素间的相关性,最后传输初始载体图像.接收方以同样方式处理图像并由两者的相关性获取隐秘信息像素值,重组隐秘图像.实验表明该模型增大了隐写容量,提高了隐蔽通信的安全性.%The multi-carrier set is set up by many sub-images which is shared by carrier image, combining with image transformation algorithms, zero-steganography model based on image sharing is built. Firstly an initial carrier image is selected, according to need to share a certain number of carrier sub-images, and one or more are choosen freely as actual carrier to specific image transform then the relevance of pixels between image blocks is found out which is divided by the secret image and transformed carrier sub-images, finally the initial carrier image is transmitted. The carrier image is processed in the same way, pixel values of secret image are gotten by the relevance, and secret image is restructured by receiver. Experiments show that this model increases the steganographic capacity and improves the security of the covert communication.
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